How can you improve the scalability of your robotic process automation systems?

1 Choose the right RPA platform

Not all RPA platforms are created equal. Some may offer more features, flexibility, and integration options than others. When choosing an RPA platform, you should look for one that supports your current and future automation needs, such as cloud-based deployment, distributed architecture, centralized management, and intelligent automation. You should also compare the costs, benefits, and risks of different platforms and select one that fits your budget and goals.

2 Design scalable workflows

The way you design your workflows can have a significant impact on the scalability of your RPA systems. You should follow the best practices of RPA development, such as defining clear inputs, outputs, and exceptions, modularizing and reusing components, documenting and testing your code, and applying version control and change management. You should also avoid hard-coding values, using unnecessary delays, and relying on screen coordinates or pixel colors. Instead, you should use dynamic selectors, variables, and data tables to make your workflows more adaptable and robust.

3 Monitor and optimize performance

To ensure that your RPA systems are running smoothly and efficiently, you should monitor and optimize their performance regularly. You should use the tools and metrics provided by your RPA platform to track the status, availability, and utilization of your robots, as well as the throughput, quality, and errors of your processes. You should also use analytics and feedback to identify bottlenecks, errors, and opportunities for improvement. You should then apply corrective and preventive actions, such as updating your workflows, adding or removing robots, or adjusting your schedules and priorities.

4 Leverage artificial intelligence

Artificial intelligence (AI) can enhance the capabilities and scalability of your RPA systems. AI can help you automate more complex, cognitive, and variable tasks that require human-like skills, such as natural language processing, image recognition, sentiment analysis, and decision making. AI can also help you learn from your data, discover new insights, and improve your processes over time. You can integrate AI with your RPA systems by using pre-built or custom-built models, APIs, or platforms that offer AI services.

5 Plan for growth and change

Finally, you should plan for the growth and change of your RPA systems. You should anticipate the future demand for automation, the potential impact of new technologies, and the possible changes in your business environment. You should also establish a governance framework that defines the roles, responsibilities, and rules for managing your RPA systems. You should also create a roadmap that outlines your vision, objectives, and milestones for scaling your RPA systems. By planning ahead, you can ensure that your RPA systems are aligned with your business strategy and ready for any challenges or opportunities.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?